Using Physiologically Based Pharmacokinetic Modeling to Assess the Risks of Failing Bioequivalence Criteria: a Tale of Two Ibuprofen Products

Loisios-Konstantinidis, Ioannis; Hens, Bart; Mitra, Amitava; Kim, Sarah; Chiann, Chang; Cristofoletti, Rodrigo

doi:10.1208/s12248-020-00495-4

Cited by 13 publications

(10 citation statements)

References 31 publications

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“…Since the observed T / R geometric mean ratios were not available in the literature, the arithmetic mean was applied to substitute for the geometric mean (eq ). R normalp normalr normale normald / normalo normalb normals = normalp normalr normale normald normali normalc normalt normale normald .25em T / R .25em normala normalr normali normalt normalh normalm normale normalt normali normalc .25em normalm normale normala normaln .25em normalr normala normalt normali normalo normalo normalb normals normale normalr normalv normale normald .25em T / R .25em normala normalr normali normalt normalh normalm normale normalt normali normalc .25em normalm normale normala normaln .25em normalr normala normalt normali normalo …”

Section: Methodsmentioning

confidence: 99%

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Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1–4 by Virtual Bioequivalence Model

Zhang

Wu³

et al. 2022

Mol. Pharmaceutics

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To evaluate the influence of solubility and permeability on the pharmacokinetic prediction performance of orally administered drugs using avirtual bioequivalence (VBE) model, a total of 23 orally administered drugs covering Biopharmaceutics Classification System (BCS) classes 1−4 were selected. A VBE model (i.e., a physiologically based pharmacokinetic model integrated with dissolution data) based on a B 2 O simulator was applied for pharmacokinetic (PK) prediction in a virtual population. Parameter sensitivity analysis was used for input parameter selection. The predictive performances of PK parameters (i.e., AUC 0−t , C max , and T max ), PK profiles, and bioequivalence (BE) results were evaluated using the twofold error, average fold error (AFE), absolute average fold error (AAFE), and BE reassessment metrics. All models successfully simulated the mean PK profiles, with AAFE < 2 and AFE ranging from 0.58 to 1.66. As for the PK parameters, except for the time of peak concentration, T max , of isosorbide mononitrate, other simulated PK parameters were all within a twofold error. The simulated PK behaviors were comparable to the observed ones, both for test (T) and reference (R) products, and the simulated T/R arithmetic mean ratios were all within 0.88−1.16 of the observed values. These four evaluation metrics were distributed equally among BCS class 1−4 drugs. The VBE model showed powerful performance to predict the PK behavior of orally administered drugs with various combinations of solubility and permeability, irrespective of the BCS category.

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Section: Methodsmentioning

confidence: 99%

“…Since the observed T / R geometric mean ratios were not available in the literature, the arithmetic mean was applied to substitute for the geometric mean (eq ). …”

Section: Methodsmentioning

confidence: 99%

Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1–4 by Virtual Bioequivalence Model

Zhang

Wu³

et al. 2022

Mol. Pharmaceutics

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“…Therefore, unless a drug product has both release/dissolution and absorption rate invariant to physiological variability, the need to consider variability applies equally to the biopharmaceutic component, as it does to other disposition parameters. Furthermore, in the context of the development of CRDSs (e.g., [ 30 , 42 ]), and where the aim is to identify dissolution safe space, VBE analysis can or indeed should be applied to provide statistical and scientific rigour. An inherent requirement to demonstrate BE, or non-bioequivalence, using widely applied crossover studies, is to be able to handle both between-subject (population) variability and within-subject variability (BSV and WSV, respectively) of PK (FDA Guidance, 2003 and 2021, for example).…”

Section: Summary Of Webinarsmentioning

confidence: 99%

Developing Clinically Relevant Dissolution Specifications (CRDSs) for Oral Drug Products: Virtual Webinar Series

McAllister

Flanagan

Cole³

et al. 2022

Pharmaceutics

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A webinar series that was organised by the Academy of Pharmaceutical Sciences Biopharmaceutics focus group in 2021 focused on the challenges of developing clinically relevant dissolution specifications (CRDSs) for oral drug products. Industrial scientists, together with regulatory and academic scientists, came together through a series of six webinars, to discuss progress in the field, emerging trends, and areas for continued collaboration and harmonisation. Each webinar also hosted a Q&A session where participants could discuss the shared topic and information. Although it was clear from the presentations and Q&A sessions that we continue to make progress in the field of CRDSs and the utility/success of PBBM, there is also a need to continue the momentum and dialogue between the industry and regulators. Five key areas were identified which require further discussion and harmonisation.

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“…Several reports have highlighted the need for better handling and estimation of WSV (4,12,(22)(23)(24). However, a best practice approach is still lacking while clinical measures of WSV in most GI parameters are unavailable.…”

Section: Introductionmentioning

confidence: 99%

“…One of the emerging applications of the PBPK models is the conduct of virtual bioequivalence (VBE) studies ( 2 ). This is associated with the advancements in mechanistic representation of oral drug absorption that enables assessment of relative bioavailability between two formulations in the same group of subjects ( 3 , 4 ) or same formulation under different conditions ( 5 , 6 ) or in different populations ( 7 ). Using PBPK modelling for biopharmaceutics analysis has transitioned from ‘academic nicety to regulatory necessity’ over the last decade ( 8 ).…”

Section: Introductionmentioning

confidence: 99%

Proof of Concept in Assignment of Within-Subject Variability During Virtual Bioequivalence Studies: Propagation of Intra-Subject Variation in Gastrointestinal Physiology Using Physiologically Based Pharmacokinetic Modeling

Bego

Patel

Cristofoletti

et al. 2022

AAPS J

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While the concept of ‘Virtual Bioequivalence’ (VBE) using a combination of modelling, in vitro tests and integration of pre-existing data on systems and drugs is growing from its infancy, building confidence on VBE outcomes requires demonstration of its ability not only in predicting formulation-dependent systemic exposure but also the expected degree of population variability. The concept of variation influencing the outcome of BE, despite being hidden with the cross-over nature of common BE studies, becomes evident when dealing with the acceptance criteria that consider the 90% confidence interval (CI) around the relative bioavailability. Hence, clinical studies comparing a reference product against itself may fail due to within-subject variations associated with the two occasions that the individual receives the same formulation. In this proof-of-concept study, we offer strategies to capture the most realistic predictions of CI around the pharmacokinetic parameters by propagating physiological variations through physiologically based pharmacokinetic modelling. The exercise indicates feasibility of the approach based on comparisons made between the simulated and observed WSV of pharmacokinetic parameters tested for a clinical bioequivalence case study. However, it also indicates that capturing WSV of a large array of physiological parameters using backward translation modelling from repeated BE studies of reference products would require a diverse set of drugs and formulations. The current case study of delayed-release formulation of posaconazole was able to declare certain combinations of WSV of physiological parameters as ‘not plausible’. The eliminated sets of WSV values would be applicable to PBPK models of other drugs and formulations.

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Using Physiologically Based Pharmacokinetic Modeling to Assess the Risks of Failing Bioequivalence Criteria: a Tale of Two Ibuprofen Products

Cited by 13 publications

References 31 publications

Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1–4 by Virtual Bioequivalence Model

Predicting the Pharmacokinetics of Orally Administered Drugs across BCS Classes 1–4 by Virtual Bioequivalence Model

Developing Clinically Relevant Dissolution Specifications (CRDSs) for Oral Drug Products: Virtual Webinar Series

Proof of Concept in Assignment of Within-Subject Variability During Virtual Bioequivalence Studies: Propagation of Intra-Subject Variation in Gastrointestinal Physiology Using Physiologically Based Pharmacokinetic Modeling

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